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Ohio State University
Enterprise Applications Developer 4
Databricks
Edtech.com's Summary
Ohio State University is hiring an Enterprise Applications Developer 4 to build enterprise-scale biomedical research and health data solutions for the College of Medicine’s Research Information Technology group. The role designs and optimizes large-scale data pipelines that support clinical research, population-scale analytics, and advanced computational science. It also leads performance tuning of distributed data workloads across cloud and high-performance computing environments.
Highlights
- Designs and develops enterprise-grade healthcare and research technology solutions
- Builds data pipelines operating on very large, highly complex multimodal research datasets
- Supports translational and biomedical research through secure, scalable technical solutions
- Contributes to data architecture for production-grade data engineering systems
- Works across cloud platforms including Azure and AWS
- Uses data engineering platforms such as Databricks and Fabric
- Operates in high-performance computing and supercomputing environments
- Optimizes distributed data processing through partitioning, file layout, and execution tuning
- Applies Python or Java, SQL, and distributed computing frameworks like Apache Spark
- Hybrid work permitted within the Columbus, Ohio metropolitan area, with occasional travel to campus for meetings
- Requires a bachelor's degree in a computing or data-related field and 8 years of combined software development and data engineering experience
Enterprise Applications Developer 4 Full Description
Job Title:
Enterprise Applications Developer 4
Enterprise Applications Developer 4 for The Ohio State University, College of Medicine, Research Information Technology, Columbus, Ohio. Hybrid or work-from-home permitted within the Columbus, Ohio Metropolitan Statistical area. Travel to university locations in Columbus, Ohio for meetings may be required.
Duties:
Serve as a senior individual contributor leading and executing the design, development, and optimization of complex, enterprise-scale biomedical research and health data and technology solutions that operate on very large and highly complex multimodal datasets; support translational and biomedical research by delivering secure, high-performance, and scalable technical solutions that enable clinical research, population-scale analytics, and advanced computational science; serve as a senior technical contributor to solution development for designing, developing, and maintaining complex, enterprise-grade healthcare and research technology solutions; contribute as a senior technical contributor to data architecture, with hands-on responsibility for the development and evolution of large-scale, production-grade data engineering solutions supporting healthcare and research use cases; develop and operate across cloud-based platforms (e.g., Azure, AWS), Data Engineering Platforms (e.g. Databricks, Fabric), and high-performance computing (HPC) or supercomputing environments; design and optimize distributed data processing workflows operating at significant scale; lead performance tuning and optimization efforts for large-scale distributed data processing workloads by applying advanced techniques such as partitioning strategies, file layout optimization, execution tuning, memory management, and cost-aware compute configuration; troubleshooting; stay current with emerging technologies and best practices.
Requirements:
Bachelor’s degree in Computer Science, Data Science, Software Engineering, Data Engineering, Health Informatics, or a related field; 8 years of combined professional experience in software development and data engineering. That 8 years of experience must have included all of the following: designing, building, and optimizing complex, large-scale software systems and data platforms, including advanced data pipelines operating on very large datasets in healthcare and research environments; development using back-end programming languages (such as Python or Java) and SQL, and use of distributed computing frameworks such as Apache Spark; delivery of solutions on cloud-based data engineering platforms (e.g., Databricks) and integrating workflows across scientific high-performance computing (HPC) environments. (All experience may have been part-time, concurrent, and/or concurrent with education.) Requires successful completion of a background check. EOE/AA/M/F/Vet/Disability Employer.
Location:
Hamilton Hall (0038)
Position Type:
Regular
Scheduled Hours:
40
Final candidates are subject to successful completion of a background check. A drug screen or physical may be required during the post offer process.
The university is an equal opportunity employer, including veterans and disability.
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